High Definition Map Solution

Abstract

Raw map data generated from various sensors might have gaps and other defects. Although map providers are currently working on generating highly accurate maps of public roads with a large coverage, gaps and other defects still exist in the map data and need to be identified. When it comes to autonomous vehicles, occurrences of such defects would impair the localization of the vehicle, and therefore the reliability of the autonomous driving system in the vehicle. Map features need to be validated for large discrepancies. If the differences are such that localization cannot be guaranteed, the autonomous driving system must be notified, thus returning control to the human driver. So, it is necessary to develop a methodology to fully evaluate raw map data and improve its quality (identity and fill gaps).